2 papers
cs.AI2026
From Unstructured Recall to Schema-Grounded Memory: Reliable AI Memory via Iterative, Schema-Aware Extraction
Alex Petrov, Alexander Gusak, Denis Mukha +1
Persistent AI memory is often reduced to a retrieval problem: store prior interactions as text, embed them, and ask the model to recover relevant context later. This design is usef…
cs.CL2025
LATTE: Learning Aligned Transactions and Textual Embeddings for Bank Clients
Egor Fadeev, Dzhambulat Mollaev, Aleksei Shestov +6
Learning clients embeddings from sequences of their historic communications is central to financial applications. While large language models (LLMs) offer general world knowledge,…